Pengaruh Pencahayaan terhadap Kinerja Segmentasi

Authors

  • Iman H. Kartowisatro Bina Nusantara University

DOI:

https://doi.org/10.21512/comtech.v5i1.2640

Keywords:

illumination, segmentation, probability density function

Abstract

 

Light intensity may affect the image quality of an object that can cause barriers in doing preprocessing to improve the image quality of a digital image. Furthermore, this would also be an impact on subsequent processes, such as sorting images according to the needs. Light intensity influences the reflection of light which translates into an image. This gives an impact on successful segmentation process. Examples of the success and failure of segmentation are presented in this paper.

Dimensions

Plum Analytics

References

Almaddah, A., Mae, Y., Ohara, K., Takubo, T., & Arai, T. (2011). Visual and Physical Sementation of Novel Objects. International Conference on Intelligent Robots and Systems, Sept 25-30, 807-812. San Francisco, CA, USA.

Gonzalez, R.C., & Wintz, P. (1987). Digital Image Processing. USA: Addison Wesley.

Kartowisastro, I. H. (2013). Pengaruh pencahayaan terhadap kinerja penentuan posisi objek. Submitted for Binus Journal.

Kaur, J., Agrawal, S., & Vig, R. (2012). A comparative analysis of thresholding and edge detection segmentation techniques. International Journal of Computer Applications, 39(15).

Kaushal, M., Singh, A., & Singh, B. (2010). Adapative thresholding for edge detection in grayscale images. International Journal of Engineering Science and Technology, 2(6), 2077-2082.

Takahiro, O., Sato, Y. (2006). Effects of image segmentation for approximating object appearance under near lighting. ACCV, 764-775, Springer-Verlag.

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Published

2014-06-30

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Section

Articles
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